AI Solutions Architect

With 500+ professionals and 350+ business professionals, Manatt, Phelps & Phillips, LLP (www.manatt.com), is a multidisciplinary, integrated national professional services firm known for quality and an extraordinary commitment to clients. The Firm’s groundbreaking approach—bringing together legal services, advocacy and business strategy—differentiates Manatt from its competitors and positions the Firm to provide a distinct and compelling value

The Opportunity

The AI & Solutions Architect is a senior, principal-level role responsible for defining and governing the technical vision for artificial intelligence systems across Manatt. This individual designs the firm’s enterprise AI reference architecture, determining how models are deployed, how agents are orchestrated, how AI tools integrate with firm data systems, and how security and compliance controls are enforced at the system level. The AI & Solutions Architect serves as the authoritative technical voice on AI infrastructure decisions and acts as the primary technical counterpart to AI vendors, cloud providers, and firm leadership.  The AI & Solutions Architect will partner closely with the Data Architect, AI Engineer, and other firm professionals to ensure that every AI capability built or deployed at the firm rests on a coherent, scalable, and defensible technical foundation.

Key Responsibilities:

Enterprise AI Architecture

• Design and own the firm’s enterprise AI reference architecture, including model deployment patterns, agent orchestration frameworks, and integration standards across the AI tool stack.
• Define the technical standards by which AI agents, workflows, and integrations are built, deployed, and maintained across the AI Engineering and Adoption Team.
• Evaluate emerging AI technologies, platforms, and vendors against firm architectural standards, security requirements, and strategic priorities — including PHI controls for healthcare advisory work and attorney-client privilege requirements.
• Develop and maintain architectural documentation including AI system diagrams, integration patterns, design specifications, and decision records.

Data & Integration Architecture

• Architect the secure data layer connecting firm systems — including iManage, practice management, financial, and operational platforms — to AI tools, agents, and custom-built workflows.
• Partner with the Data Architect to ensure the firm’s data infrastructure meets the access, governance, and performance requirements of AI consumption.
• Define patterns for retrieval-augmented generation (RAG), vector search, and knowledge retrieval that enable matter-aware, context-rich AI outputs.
• Oversee the technical review of vendor AI integrations, ensuring consistency with firm architecture standards and data security requirements.

Engineering Standards & Team Leadership

• Collaborate with the AI Engineer to establish coding standards, integration patterns, testing requirements, and deployment pipelines for all custom AI development.
• Define observability, monitoring, and quality standards for AI systems in production, ensuring reliability and auditability across deployed capabilities.
• Mentor and guide AI Engineers and AI Solutions Analysts on architectural best practices, fostering a culture of technical rigor and continuous improvement.
• Stay current on developments in AI infrastructure, foundation models, and enterprise AI platforms, translating emerging capabilities into actionable recommendations for firm leadership.

Stakeholder Engagement

• Serve as technical advisor to the AI Program Lead and firm leadership on AI capability investments, sequencing, build-versus-buy decisions, and risk.
• Translate complex architectural decisions into clear, accessible language for non-technical stakeholders including practice group chairs and executive leadership.
• Collaborate cross-functionally with Information Security, Privacy, Risk, and Legal Operations to ensure AI systems are defensible, compliant, and aligned with firm policy.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems, or a related field.
• 8+ years of experience in solutions architecture, enterprise software engineering, or AI/ML engineering, with a demonstrated track record of designing production AI systems.
• Deep expertise in LLM-powered application architecture, including RAG pipelines, AI agent frameworks, and multi-mo…